code: def test_grad_scaler_kwargs(self):
      # If no defaults are changed, `to_kwargs` returns an empty dict.
      scaler_handler = GradScalerKwargs(
          init_scale=1024, growth_factor=2
      )
      AcceleratorState._reset_state()
      accelerator = Accelerator(
          mixed_precision="fp16", kwargs_handlers=[scaler_handler]
      )
      print(accelerator.use_fp16)
      scaler = accelerator.scaler
  
      # Check the kwargs have been applied
      self.assertEqual(scaler._init_scale, 1024.0)
      self.assertEqual(scaler._growth_factor, 2.0)
  
      # Check the other values are at the default
      self.assertEqual(scaler._backoff_factor, 0.5)
      self.assertEqual(scaler._growth_interval, 2000)
      self.assertEqual(scaler._enabled, True)
  
file_path: accelerate/tests/test_kwargs_handlers.py
imports: import inspect
  import os
  import unittest
  from dataclasses import dataclass
  import torch
  from accelerate import Accelerator, DistributedDataParallelKwargs, GradScalerKwargs
  from accelerate.state import AcceleratorState
  from accelerate.test_utils import execute_subprocess_async, require_cuda, require_multi_gpu
  from accelerate.utils import AutocastKwargs, KwargsHandler, TorchDynamoPlugin, clear_environment
label_desc: Use image node_id 2 for calling the KwargsHandlerTester obj's underlying member method code with example usage: obj.test_grad_scaler_kwargs() without return types